Method and system for pulse diagnosis

ABSTRACT

A process is described for diagnosing mammalian patients, including human patients, based on the spatial and temporal profile of the radial arterial pulse. Pulse patterns are measured, and the patterns and matching diagnoses added to an analytic module including a database system.

BACKGROUND Description of the Related Art

Sphygmology is highly desirable as a tool, with sense and simplicity, inexpensive, and accessible leading to substantial diagnostic yield. (van Tellingen C. De pulsibus-or sense and simplicity in daily medical practice. Int J Cardio1. 2010;142:201-6.) Despite this, sphygmology has been largely abandoned by Western medicine even though taking your pulse is still a routine part of most doctor's visits. The rate and strength of a pulse can be used to determine hydration, arterial blockage, levels of fitness, systolic blood pressure, heart failure, hypertrophic obstructive cardiomyopathy, hyperdynamic circulation, cardiac tamponade, pericarditis, chronic sleep apnea, croup, and obstructive lung disease. Recent Western research has indicated that severe aortic stenosis may be associated with a weak and delayed pulse; a bifid systolic pulse can be produced in some obstructive cardiomyopathies; a bounding pulse indicates a large stroke volume with a rapid fall-off, occurring in hyperkinetic states, such as fever, anemia and thyrotoxicosis. (Libby P, Bonow R O, Mann D L, Libby P. 8th ed. Philadelphia: Saunders Elsevier; 2008. Braunwald's heart diseases.)

Sphygmology is still an important part of some traditional medicine systems. According to the practice, each pulse consists of four parts, an expansion followed by a pause and a contraction followed by a second pause. Ten criteria are used to evaluate the pulse, size, fastness or slowness, strength or weakness, shortness or length of pulse intervals, softness or hardness, similarity or dissimilarity, regularity or irregularity in diverse pulses and harmony related to musical nature of the pulse. (Ibn Sina. Tehran: Selsele Intisharat-e Anjomane Asare Melli; 1951.)

Pulse diagnosis is a quick, inexpensive, and non-invasive diagnostic tool. When performed by trained professionals, it can be an effective means for determining patient's health. However, pulse diagnosis requires sensitivity and skill and has been generally supplanted by modern technology such as EKG reading or echocardiograph as its accuracy frequently depends on the knowledge and the experience of the practitioner. There is therefore a need for a means for consistently relating a pulse to a specific diagnosis that is not dependent on the knowledge and experience of the practitioner.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced.

FIG. 1 is a system diagram of an embodiment of a system for pulse based diagnosis.

FIG. 2 is an action flow diagram of an embodiment of a process for utilizing a system for pulse diagnosis.

FIG. 3 is a flow chart of an embodiment of a process for utilizing a system for pulse diagnosis.

FIG. 4 is a system diagram of an embodiment of a system for pulse based diagnosis.

FIG. 5 is an action flow diagram of an embodiment of a process for utilizing a system for pulse based diagnosis.

FIG. 6 is a flow chart of an embodiment of a process for utilizing a system for pulse based diagnosis.

FIG. 7 is an embodiment of a pulse sensing and remote telemetry device.

FIG. 8 is an embodiment a machine system to implement a pulse measurement system in an institutional setting.

FIG. 9 is an embodiment of a computer system machine and a machine communication network.

DETAILED DESCRIPTION Glossary

“Database” in this context refers to an organized collection of data (states of matter representing values, symbols, or control signals to device logic), structured typically into tables that comprise ‘rows’ and ‘columns’, although this structure is not implemented in every case. One column of a table is often designated a ‘key’ for purposes of creating indexes to rapidly search the database.

“Module” in this context refers to logic having boundaries defined by function or subroutine calls, branch points, application program interfaces (APIs), or other technologies that provide for the partitioning or modularization of particular processing or control functions. Modules are typically combined via their interfaces with other modules to carry out a machine process.

“Portal” in this context refers to a web site or other network component that offers an aggregation of resources and services, such as e-mail, forums, search engines, and online shopping.

“Profile” in this context refers to a machine memory organization representing a set of correlated values associated with a physical thing (object, person, etc.)

“Sensor” in this context refers to a device or composition of matter that responds to a physical stimulus (as heat, light, sound, pressure, magnetism, or a particular motion) and transmits a resulting impulse (as for measurement or operating a control)

“Web page” in this context refers to a file configured for access and display via a web browser over the Internet, or Internet-compatible networks. Also, logic defining an information container that is suitable for access and display using Internet standard protocols. Content defined in a web page is typically accessed using a web browser, and displayed. Web pages may provide navigation to other web pages or content via hypertext links. Web pages frequently subsume other resources such as style sheets, scripts and images into their final presentation. Web pages may be retrieved for display from a local storage device, or from a remote web server via a network connection.

Description

Coronary heart disease and stroke are the top two killers of people throughout the world. Worldwide, 3.2 million people die annually, with treatment costs rising to US $151.9 billion annually. Early warning signs are often missed until a patent is symptomatic or has a heart attack.

Traditional Chinese Medicine (TCM) has the potential of providing an early warning system of cardiovascular and other diseases, in addition to therapy protocols using herbal medicine. TCM using pulse diagnosis has been practiced for over 2000 years. However, TCM is not appreciated or used widely in western medical practice, partly due to a large variability in TCM diagnosis and treatments.

Described herein is a system that builds on TCM practice to provide a low cost, accurate warning and diagnosis system for assessing cardiovascular disease. The system provides an early warning system for stoke and heart attack so that intervention is possible. The system utilizes pulse tectonics to characterize and interpret blood flow dynamics of the cardiovascular system, and to promote health and wellness and as early warning system for cardiovascular disease including stroke and heart attacks. The system includes sensors for the acquisition of the dynamic properties of arterial pulse that represent the functioning of the cardiovascular system including the heart, blood, and its interaction and profusion through the blood vessels, tissue and organs. The collected signals are processed to diagnose various health-related conditions.

Sensors are employed for the acquisition of pulse information. Interpretation of pulse information follows. The system deconstructs data acquired by a TCM practitioner to build a database of TCM diagnosis related to the acquired pulse waveforms. The system compares new patient pulse waveforms with patterns in the database to determine a most likely diagnosis, and supplements efficacy of comparison with computer models. The database may be built utilizing a number of approaches, or combinations of these approaches. In one embodiment, “feel through” sensors are employed to collect time/pressure measurements during actual diagnostics of patients by human practitioners. Due to problems with noise (from the pulse of the practitioner), this approach may be utilized as a first pass to later stages that refine the measurements. In another embodiment (which may supplement the “feel through sensor” technique), a visual and/or auditory representation of the pressure vs time characteristics of the pulse may be provided to the practitioner. This enables the practitioner to see and hear what they feel through the sensors, providing validation and additional interpretation of the signals. In another embodiment (which may supplement either or both of the others), a cuff is utilized on the patient to collect measurements. The cuff does not suffer interference/noise from pulse signals of the practitioner, and thus may provide very accurate readings.

The system is non invasive, low cost, and provides an early warning system for cardiovascular and associated diseases when intervention can be most effective.

Measurements collected or characteristics identified from measurements include pulse transit time (reflectometry), blood flow dynamics (strength of the heart), arterial stiffness (cardiac efficiency), and blood viscosity.

The system may be utilized to diagnose a number of conditions, including coronary ischemia, heart valve function, heart muscle inflammation, mitral valve problems, bundle branch blockages, tricuspid valve problems, high blood pressure, aortic valve problems, irregular heart beat, aortic insufficiency, atrial fibrillation, small vessel blockage, tachycardia, weak heart, bradycardia, enlarged heart, congestive heart, coronary aneurism (hematoma), and arterial stiffness. The system may include a TCM waveform database comprising visual and acoustic representations of signal waveforms indicative of various conditions.

The system may be utilized to diagnose mammalian patients, especially human patients, based on a spatial and temporal profile of the radial arterial pulse. The patterns of the pulse may be measured by any means generally used including manually and/or with the use of sensors or other electronic or medical devices. Pulse patterns and matching diagnoses may added to the database through system modeling, practitioner input, known diagnoses, known patterns, echocardiograms, mechanical instrumentation or a combination thereof. The pulse pressure, shape, flow, depth, rate, regularity, width, length, smoothness, stiffness, and strength of a patient are measured and the pattern of the pulse is entered into the database. The patient's pulse pattern is compared to pulse patterns in the database with recorded diagnoses, and a diagnosis is rendered.

A layout of pressure sensors along a blood vessel may provide the system with a complete description of the three dimensional undulation of the vessel along an arm, leg, or other area of the body (typically, an arm). A pressure wave through the area is measured and correlated versus a timing signal (pressure wave vs time). This pressure wave is further correlated with cardiac events (typically, heart beats). Signal processing is applied to the collected data set and correlations to identify and quantify pressure reflections, timing of reflections, and the amplitude and phase of reflections with respect to primary waves and possibly also with respect to one another.

A data input module receives data from the layout of pressure sensors along the blood vessel, and provides the data to a signal processing module. The signal processing module applies the data to determine a description of the three dimensional undulation of the vessel and to identify the pressure wave versus time, and to correlate the pressure wave with cardiac events, as described above. The signal processing module identifies and quantifies pressure reflections, timing of reflections, and the amplitude and phase of reflections with respect to primary waves and possibly also with respect to one another. All of this information may then be compared against stored patterns in a diagnostic database, for a best fit with known pathological “signatures” (e.g., a blocked artery somewhere in the body). The collected data and analysis may be sufficient to identify the pathology very specifically (e.g., blockage, extent of blockage, and location of blockage in the body), or only generally (e.g., a blockage somewhere in the body). An appropriate treatment plan may then be formulated.

As used herein, depth of the pulse is the vertical position of the arterial pulse below the measurement surface (e.g., skin), and is rated along a continuum. Rate is the number of beats in a minute. Regularity is the rhythm of the arterial pulse, which is categorized as either regular or irregular. Width is the intensity of the arterial pulse. Length is the range of the arterial pulse that can be sensed. Smoothness is the slickness of the arterial pulse. Stiffness is the elasticity of the radial artery. Finally, strength is the forcefulness of the arterial pulse relative to the change in pressure applied.

The pulse wave form is assessed at one or more depths, specifically a superficial, middle and/or deep level. A superficial level is directly below the skin level and is located by resting sensors or fingers directly above the radial artery. The only pressure exerted being passive weight. The deep level is situated directly above the surface of the radius. It is located by first occluding the radial artery by exerting heavy pressure upon the artery, pushing it against the surface of the radius until the pulsations cease and then slowly releasing the pressure until the pulsation returns. This type of occlusion causes a subsequent initial rush in the blood flow, rendering it necessary to allow a few seconds for the pulse to equalize, while maintaining the same finger pressure, before pulse assessment continues. The middle level is located midway between the superficial and deep levels. (King et al., ACUPUNCTURE IN MEDICINE 2002;20(4):150-159).

In some embodiments, the pulse pattern is measured by a practitioner by any means generally used. In some embodiments, a clinician may place their index, middle and ring finger on the wrist of a patient over the radial artery. The index finger may be placed below the wrist bone on the thumb side of the patient's hand with the middle finger and ringer finger placed next to the index finger. The clinician may enter a description of the pulse pattern into the database to determine a diagnosis. In some embodiments, a written description is entered. In other embodiments, a verbal description is entered. In yet another embodiment the wave form or pulse wave may be graphically recorded and entered into the database.

In some embodiments, the pulse pattern is collected by sensors on the practitioner's finger. A practitioner may wear one or more sensors on one or more fingers. In some embodiments, sensors are worn on the index, middle and ring fingers, or a combination thereof. In further embodiments, multiple sensors may be worn on each finger. In another embodiment, sensors may be included in a cuff or sleeve which is put around a patient's arm. Sensors may be in a linear array or a series of linear arrays along the finger and/or across the hand. Microdisplacements resulting from the transfer of the pulse undulations under the skin may in some implementations be measured by the interference of coherent light from the surface of the skin without contact as viewed by a video camera as laser speckle. Microdisplacements resulting on the surface of the skin may in some cases be measured by processing the signal from a video camera to measure subtle movements of the skin. In all embodiment above, the sensor detects the pulse wave form as well as the amount of pressure used to measure the pulse. The sensors convert the pulse to a signal that can be transmitted to an analog amplifier. The signal is converted to a digital signal and sent to a transceiver. The received signal is then sent to a digital signal processor. The signal is then sent to a database and compared to other pulse patterns. Once a match is found, the diagnosis for the patient is displayed.

In one embodiment, signal analysis on the collected sensor signals comprises time series analysis of digital signal streams, including auto-correlation, cross correlations, power spectral distribution, cross spectral distribution, Fourier Analysis, wavelet analysis, principal component analysis, root mean square matching and similar and/or custom analysis tools. These tools will reduce the pulse train into a form of eigenvalues that enable rapid comparison within large databases of patient data.

Patient data from the database can be used in various assessments for determining the health of the patient and pulse measurements may be combined with as little or as much additional patient data as desired. In some embodiments, the database may store patient related data, e.g. a patient identifier and/or patient demographic information. The database may also be able to generate reports using the report generation module. The disease management recommendations module can store various treatment recommendations that can be included in patient reports based on the analysis of the data gathered from the pulse. The comparative data store can store comparative data from healthy patients and/or patients with a chronic illness and combinations of pulse patters and diagnoses.

In some embodiments, a patient may complete a questionnaire to improve the diagnostic capabilities of the system. The questionnaires can address any of a number of health conditions. For example, in some embodiments, rating scales may be used to assess the health and mental condition of the patient. Exemplary health and mental rating scales include, but are not limited to, those discussed in: Bruett T L, Overs R P. A critical review of 12 ADL scales. Phys Ther 1969;49:857-862; Zimmer J G, Rothenberg B M, Andresen E. Functional assessment. In: Andresen E M, Rothenberg B, Zimmer J G, eds. Assessing the health status of older adults. New York: Springer, 1997:1-40; Kuriansky J, Gurland B. The performance test of activities of daily living. Int J Aging Hum Devel 1976;7:343-352; Haley S M, Ludlow L H, Gans B M, et al. Tufts Assessment of Motor Performance: an empirical approach to identifying motor performance categories. Arch Phys Med Rehabil 1991;72:359-366; Hamilton M. Diagnosis and rating of anxiety. Br J Psychiatry 1969; Special Publication #3:76-79. Taylor J A. A personality scale of manifest anxiety. J Abnorm Soc Psychol 1953;48:285-290; Salisbury J L, Sherrill D, Friedman S T, et al; Comparison of two scoring methods for the short form of the Manifest Anxiety Scale and Eysenck's Extraversion (E) and Neuroticism (N) scales. Psychol Rep 1968;22:1235-1236; Bendig A W. The development of a short form of the Manifest Anxiety Scale. J Consult Psychol 1956;20:384; Reynolds C R, Richmond B O. Revised Children's Manifest Anxiety Scale (RCMAS) manual. Los Angeles: Western Psychological Services, 1985; Hamilton M. The assessment of anxiety states by rating. Br J Med Psychol 1959;32:50-55; Bech P, Kastrup M, Rafaelsen O J. Minicompendium of rating scales for states of anxiety, depression, mania, schizophrenia, with corresponding DSM-III syndromes. Acta Psychiatr Scand 1986;73 (suppl 326):1-37; Moran P W, Lambert M J. A review of current assessment tools for monitoring changes in depression. In: Lambert M J, Christensen E R, DeJulio S S, eds; Cronholm B, Schalling D, Asberg M. Development of a rating scale for depressive illness. Mod Probl Pharmacopsychiatry 1974;7:139-150; Lambert M J, Hatch D R, Kingston M D, et al. Zung, Beck, and Hamilton rating scales as measures of treatment outcome: a metaanalytic comparison. J Consult Clin Psychol 1986;54:54-59. Huppert F A, Tym E. Clinical and neuropsychological assessment of dementia. Br Med Bull 1986;42:11-18; Ramsdell J W, Rothrock J F, Ward H W, et al. Evaluation of cognitive impairment in the elderly. J Gen Intern Med 1990;5:55-64; McKhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease. Neurology 1984;34:939-944; Hersch E L, Kral V A, Palmer R B. Clinical value of the London Psychogeriatric Rating Scale. J Am Geriatr Soc 1978;26:348-354; Crockett D, Tuokko H, Koch W, et al. The assessment of everyday functioning using the Present Functioning Questionnaire and the Functional Rating Scale in elderly samples. Clin Gerontol 1989;24:3-25; Frederiksen L W, Lynd R S, Ross J. Methodology in the measurement of pain. Behav Ther 1978;9:486-488; Dalton J A, McNaull F. A call for standardizing the clinical rating of pain intensity using a 0 to 10 rating scale. Cancer Nurs 1998;21:46-49; Fordyce W E, Lansky D, Calsyn D A, et al. Pain measurement and pain behavior. Pain 1984;18:53-69. According to some embodiments, the questionnaires can be implemented on a web portal and the user is presented with a web page or series of web pages that present the questionnaire to the patient and capture the patient's response. The responses may be stored with the patient profile and combined with other patient information or transmitted to the clinician for use when analyzing a diagnosis and determining a course of treatment.

The techniques and procedures described herein may be implemented via logic distributed in one or more computing devices. The particular distribution and choice of logic may vary according to implementation.

Those having skill in the art will appreciate that there are various logic implementations by which processes and/or systems described herein can be effected (e.g., hardware, software, and/or firmware), and that the preferred vehicle will vary with the context in which the processes are deployed. “Software” refers to logic that may be readily readapted to different purposes (e.g. read/write volatile or nonvolatile memory or media). “Firmware” refers to logic embodied as read-only memories and/or media. Hardware refers to logic embodied as analog and/or digital circuits. If an implementer determines that speed and accuracy are paramount, the implementer may opt for a hardware and/or firmware vehicle; alternatively, if flexibility is paramount, the implementer may opt for a solely software implementation; or, yet again alternatively, the implementer may opt for some combination of hardware, software, and/or firmware. Hence, there are several possible vehicles by which the processes described herein may be effected, none of which is inherently superior to the other in that any vehicle to be utilized is a choice dependent upon the context in which the vehicle will be deployed and the specific concerns (e.g., speed, flexibility, or predictability) of the implementer, any of which may vary. Those skilled in the art will recognize that optical aspects of implementations may involve optically-oriented hardware, software, and or firmware.

The foregoing detailed description has set forth various embodiments of the devices and/or processes via the use of block diagrams, flowcharts, and/or examples. Insofar as such block diagrams, flowcharts, and/or examples contain one or more functions and/or operations, it will be understood as notorious by those within the art that each function and/or operation within such block diagrams, flowcharts, or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof Several portions of the subject matter described herein may be implemented via Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), digital signal processors (DSPs), or other integrated formats. However, those skilled in the art will recognize that some aspects of the embodiments disclosed herein, in whole or in part, can be equivalently implemented in standard integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more processors (e.g., as one or more programs running on one or more microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and/or writing the code for the software and/or firmware would be well within the skill of one of skill in the art in light of this disclosure. In addition, those skilled in the art will appreciate that the mechanisms of the subject matter described herein are capable of being distributed as a program product in a variety of forms, and that an illustrative embodiment of the subject matter described herein applies equally regardless of the particular type of signal bearing media used to actually carry out the distribution. Examples of a signal bearing media include, but are not limited to, the following: recordable type media such as floppy disks, hard disk drives, CD ROMs, digital tape, and computer memory.

In a general sense, those skilled in the art will recognize that the various aspects described herein which can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or any combination thereof can be viewed as being composed of various types of “circuitry.” Consequently, as used herein “circuitry” includes, but is not limited to, electrical circuitry having at least one discrete electrical circuit, electrical circuitry having at least one integrated circuit, electrical circuitry having at least one application specific integrated circuit, circuitry forming a general purpose computing device configured by a computer program (e.g., a general purpose computer configured by a computer program which at least partially carries out processes and/or devices described herein, or a microprocessor configured by a computer program which at least partially carries out processes and/or devices described herein), circuitry forming a memory device (e.g., forms of random access memory), and/or circuitry forming a communications device (e.g., a modem, communications switch, or optical-electrical equipment).

Those skilled in the art will recognize that it is common within the art to describe devices and/or processes in the fashion set forth herein, and thereafter use standard engineering practices to integrate such described devices and/or processes into larger systems. That is, at least a portion of the devices and/or processes described herein can be integrated into a network processing system via a reasonable amount of experimentation.

The foregoing described aspects depict different components contained within, or connected with, different other components. It is to be understood that such depicted architectures are merely exemplary, and that in fact many other architectures can be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively “associated” such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality can be seen as “associated with” each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated can also be viewed as being “operably connected”, or “operably coupled”, to each other to achieve the desired functionality.

DRAWINGS

FIG. 1 is a system diagram of an embodiment of a system for pulse based diagnosis. FIG. 2 is an action flow diagram of an embodiment of a process for utilizing a system for pulse diagnosis. FIG. 3 is a flow chart of an embodiment of a process for utilizing a system for pulse diagnosis. The system comprises Clinician 102, Sensor 104, Modeling 106, database 108, and Diagnostic module 112. The database 108 receives a reading signal from the Sensor 104 and in response searches for a pattern match based on signal received (302). The database 108 receives an input signal from the Clinician 102 and in response searches for a pattern match based on signal received (304). The database 108 receives an input signal from the Modeling 106 and in response searches for a pattern match based on signal received (306). The Diagnostic module 112 receives a data set signal from the database 108 and in response displays the diagnosis (308).

FIG. 4 is a system diagram of an embodiment of a system for pulse based diagnosis. FIG. 5 is an action flow diagram of an embodiment of a process for utilizing a system for pulse based diagnosis. FIG. 6 is a flow chart of an embodiment of a process for utilizing a system for pulse based diagnosis. Together these drawings illustrate a system of logic components that produce a diagnostic assessment/report from patient data, comparative data, stored treatments and diagnostic data. The system comprises Patient profile memory 402, Diagnostic data memory 406, diagnostics/reporting module 408, Disease management memory 410, and Comparative data memory 412. The diagnostics/reporting module 408 receives a treatments signal from Disease management memory 410, a patient data signal from Patient profile memory 402, a comparative data signal from Comparative data memory 412, and a diagnostic data signal from Diagnostic data memory 406 and in response generates a diagnostic assessment (diagnosis)/report (see 602, 604, 606, and 608).

FIG. 7 illustrates a device 700 that may implement an embodiment of a pulse sensing and remote telemetry device. Logic 720 provides device system control over other components and coordination between those components as well as signal processing for the device. Signal processing and system control logic 720 extracts baseband signals from the radio frequency signals received by the device, and processes baseband signals up to radio frequency signals for communications transmitted from the device. Logic 720 may comprise a central processing unit, digital signal processor, and/or one or more controllers or combinations above these components. The device may further comprise memory 708 which may be utilized by the central processors, digital signal processors in controllers of the systems logic 720. The device 700 may include sensor(s) 710 to detect and measure pulse signals, for example pressure and/or audio sensors, in the manners already described.

Images, video and other display information, for example, user interface optical patterns, may be output to a display module 730 which may for example operate as a liquid crystal display or may utilize other optical output technology. The display module 730 may also operate as a user input device, being touch sensitive where contact or close contact by a use's finger or other device handled by the user may be detected by transducers. An area of contact or proximity to the display module 730 may also be detected by transducers and this information may be supplied to the control logic 720 to affect the internal operation of the mobile device 700 and to influence control and operation of its various components.

Audio signals may be provided to an audio circuit 722 from which signals output to one and more speakers to create pressure waves in the external environment representing the audio.

The device 700 may operate on power received from a battery 716. The battery capability and energy supply may be managed by a power management module 718.

Another user interface device operated by control logic 720 is a keypad 728 which responds to pressure or contact events by a user of the device. As noted the keypad may in some cases be implemented by transducers of the display module 730.

The device 700 may generate short range wireless signals to influence other devices in its proximity, and may receive wireless signals from those proximate devices using antenna 736. Short range radio signals may influence the device, or be generated by the device for output to the environment, through a BlueTooth, WiFi or other RF module 726. Other forms of electromagnetic radiation may be used to interact with proximate devices, such as infrared (not illustrated). The device 700 may convert audio phenomenon from the environment into internal electro or optical signals by using microphone and the audio circuit 722.

FIG. 8 illustrates an embodiment a machine system to implement a pulse measurement system in an institutional setting. An IP sensor 810 responds to a physical stimulus from the environment with output signals that represent the physical stimulus (see description of possible sensors for a pulse measurement system). The signal is output in Internet Protocol (IP) format (for example), and propagated via a router 814 and a bridge 818 to a server system. Another sensor 812 does not have IP protocol capability and so outputs signals in a different (e.g., analog or non-IP digital) format to an IP-enabled device 820 which converts the signals output by the sensor 812 into an IP protocol and communicates them via a router 816 and bridge 818 to the server system. The server system in this example comprises a number of separate server devices, typically each implemented in the separated machine, although this is not necessarily the case. The signals from the sensors are provided via a load balancing server 808 to one or more application server 804 and one or more database server 816. Load balancing server 808 maintains an even load distribution to the other server, including web server 802, application server 804, and database server 806. In one implementation of a pulse measurement system, the application server 804 may implement an analytic/diagnostic/reporting system and the database server 806 may implement one or more data storage components as described for example in conjunction with FIG. 4. Each server in the drawing may represent in effect multiple servers of that type. The signals from the sensors 810, 812 influence one or more processors of the application server 804 to carry out various transformations for pulse diagnosis. Database server 806 may provide signals in response to resource requests indicative of stored patient data, comparative data, diagnostic data, and disease management data. The signals applied to the database server 806 may cause the database server 806 to access and certain memory addresses, which correlates to certain rows and columns in a memory device. These signals from the database server 806 may also be applied to application server 804 via the load balancing server 808. The system may supply signals to the web server 802, which in turn converts the signals to resources available via the Internet or other WAN by devices of users of the system (client devices).

FIG. 9 illustrates an embodiment of a computer system machine and a machine communication network. The computer system 900 may implement an embodiment of a pulse diagnostic system as described herein, for example one or more of the components of FIG. 1, 4, or 8. A particular computer system 900 of the machine network may include one or more processing units 912, a system memory 914 and a system bus 916 that couples various system components including the system memory 914 to the processing units 912. The processing units 912 may be any logic processing unit, such as one or more central processing units (CPUs), digital signal processors (DSPs, application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), etc. The system bus 916 can employ any known bus structures or architectures, including a memory bus with memory controller, a peripheral bus, and a local bus. The system memory 914 includes read-only memory (ROM) 918 and random access memory (RAM) 920. A basic input/output system (BIOS) 922, which can form part of the ROM 918, contains basic routines that help transfer information between elements within the computer system 900, such as during start-up.

The computer system 900 may also include a plurality of interfaces such as network interface 960, interface 958 supporting modem 957 or any other wireless/wired interfaces.

The computer system 900 may include a hard disk drive 924 for reading from and writing to a hard disk 925, an optical disk drive 926 for reading from and writing to removable optical disks 930, and/or a magnetic disk drive 928 for reading from and writing to magnetic disks 932. The optical disk 930 can be a CD-ROM, while the magnetic disk 932 can be a magnetic floppy disk or diskette. The hard disk drive 924, optical disk drive 926 and magnetic disk drive 928 may communicate with the processing unit 912 via the system bus 916. The hard disk drive 924, optical disk drive 926 and magnetic disk drive 928 may include interfaces or controllers (not shown) coupled between such drives and the system bus 916, as is known by those skilled in the relevant art. The drives 924, 926 and 928, and their associated computer-readable storage media 925, 930, 932, may provide non-volatile and non-transitory storage of computer readable instructions, data structures, program modules and other data for the computer system 900. Although the depicted computer system 900 is illustrated employing a hard disk 924, optical disk 926 and magnetic disk 928, those skilled in the relevant art will appreciate that other types of computer-readable storage media that can store data accessible by a computer may be employed, such as magnetic cassettes, flash memory, digital video disks (DVD), Bernoulli cartridges, RAMs, ROMs, smart cards, etc. For example, computer-readable storage media may include, but is not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, compact disc ROM (CD-ROM), digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, solid state memory or any other medium which can be used to store the desired information and which may be accessed by processing unit 912.

Program modules can be stored in the system memory 914, such as an operating system 934, one or more application programs 936, other programs or modules 938 and program data 940. Application programs 936 may include instructions that cause the processor(s) 912 to automatically provide dynamic selection of data and telecommunication service providers before or during communications between various devices such as, for example, a mobile device and a landline telephone. Other program modules 938 may include instructions for handling security such as password or other access protection and communications encryption. The system memory 914 may also include communications programs, for example, a Web client or browser 941 for permitting the computer system 900 to access and exchange data with sources such as Web sites of the Internet, corporate intranets, extranets, or other networks and devices as described herein, as well as other server applications on server computing systems. The browser 941 in the depicted embodiment is markup language based, such as Hypertext Markup Language (HTML), Extensible Markup Language (XML) or Wireless Markup Language (WML), and operates with markup languages that use syntactically delimited characters added to the data of a document to represent the structure of the document. A number of Web clients or browsers are commercially available such as those from Mozilla, Google, and Microsoft.

Although illustrated as being stored in the system memory 914, the operating system 934, application programs 936, other programs/modules 938, program data 940 and browser 941 can be stored on the hard disk 925 of the hard disk drive 924, the optical disk 930 of the optical disk drive 926 and/or the magnetic disk 932 of the magnetic disk drive 928.

An operator can enter commands and information into the computer system 900 through input devices such as a touch screen or keyboard 942 and/or a pointing device such as a mouse 944, and/or via a graphical user interface. Other input devices can include a microphone, joystick, game pad, tablet, scanner, etc. These and other input devices are connected to one or more of the processing units 912 through an interface 946 such as a serial port interface that couples to the system bus 916, although other interfaces such as a parallel port, a game port or a wireless interface or a universal serial bus (USB) can be used. A monitor 948 or other display device is coupled to the system bus 916 via a video interface 950, such as a video adapter. The computer system 900 can include other output devices, such as speakers, printers, etc.

The computer system 900 can operate in a networked environment using logical connections to one or more remote computers and/or devices. For example, the computer system 900 can operate in a networked environment using logical connections to one or more mobile devices, landline telephones and other service providers or information servers. Communications may be via a wired and/or wireless network architecture, for instance wired and wireless enterprise-wide computer networks, intranets, extranets, telecommunications networks, cellular networks, paging networks, and other mobile networks. Communication may take place between the computer system 900 and external devices via a WAN 954 or LAN 952. External devices may include other computer system 908 a-n (collectively, 908) and external storage devices 906. 

1. (canceled)
 2. (canceled)
 3. A diagnostic system, comprising: at least one processor circuit; at least one nontransitory memory communicatively coupled the at least one processor circuit and which stores at least one of processor executable instructions or data, execution of which causes the at least processor circuit to: for each of a number of visits by each of a plurality of subjects, receive respective pulse signal information representative of: i) a first pulse signal waveform captured from the respective subject at a first applied pressure at a first location and ii) at least a second pulse signal waveform captured from the respective subject a second applied pressure at the first location, the second applied pressure different than the first applied pressure, and receives diagnosis information that includes at least a primary diagnosis associated with the respective visit by the respective subject; store the received respective pulse signal information and diagnosis information to the at least one nontransitory memory; and determine one or more correlations between various ones of a number of defining characteristics of representations of the first and at least the second pulse signal waveforms and the diagnosis information.
 4. The diagnostic system of claim 3 wherein for each of the number of visits by each of the plurality of subjects, receives respective pulse signal information representative of: iii) a third pulse signal waveform captured from the respective subject at a third applied pressure at the first location, the third applied pressured different from the first and the second applied pressures.
 5. The diagnostic system of claim 4 wherein for a given one of the visits of a given one of the subjects, the received respective pulse signal information further represents a fourth, a fifth and a sixth pulse signal waveform captured from the respective subject at a first, a second and a third applied pressure, respectively, at a second location along a given artery, the second location spaced from the first location.
 6. The diagnostic system of claim 5 wherein for a given one of the visits of a given one of the subjects, the first, the second and the third pulse signal waveforms are captured temporally proximate to one another.
 7. The diagnostic system of claim 5 wherein for a given one of the visits of a given one of the subjects, the first, the second, the third, the fourth, the fifth and the sixth pulse signal waveforms are captured temporally proximate to one another.
 8. The diagnostic system of claim 4 wherein for the given one of the visits of the given one of the subjects, the first, the second and the third pulse signal waveforms represent pulse waveforms captured at a first location along the radial artery proximate a wrist bone on a thumb side of a hand of the subject at the first, the second and the third applied pressures, respectively, and the fourth, the fifth, and the sixth pulse signal waveforms represent pulse waveforms captured at a second location along the radial artery proximate the ulnar, at the first, the second and the third applied pressures, respectively , the second location spaced from the first location.
 9. The diagnostic system of claim 8 wherein for a given one of the visits of a given one of the subjects, the received respective pulse signal information further represents a seventh, an eight and a ninth pulse signal waveform captured from the respective subject at a first, a second and a third applied pressure, respectively, at a third location along the radial artery, the third location closely spaced from the first and the second locations.
 10. The diagnostic system of claim 9 wherein for a given one of the visits of a given one of the subjects, the first, the second, the third, the fourth, the fifth, the sixth, the seventh, the eight, and the ninth pulse signal waveforms are captured substantially concurrently with one another.
 11. The diagnostic system of claim 8 wherein the first, the second and the third pulse signal waveforms each represents respective ones of pulse waveforms captured through a skin of the given subject.
 12. The diagnostic system of claim 3 wherein the received respective pulse signal information represents digitized versions of the first and the second pulse signal waveforms.
 13. The diagnostic system of claim 3 wherein the at least one processor circuit digitizes the first and second pulse signal waveforms to generate the respective pulse signal information.
 14. A method operation in a diagnostic system that includes at least one processor circuit and at least one nontransitory memory communicatively coupled the at least one processor circuit and which stores at least one of processor executable instructions or data, the method comprising: for each of a number of visits by each of a plurality of subjects, receiving respective pulse signal information representative of: i) a first pulse signal waveform captured from the respective subject at a first applied pressure at a first location and ii) at least a second pulse signal waveform captured from the respective subject a second applied pressure at the first location, the second applied pressure different than the first applied pressure, and receives diagnosis information that includes at least a primary diagnosis associated with the respective visit by the respective subject; storing the received respective pulse signal information and diagnosis information to the at least one nontransitory memory; and determining one or more correlations between various ones of a number of defining characteristics of representations of the first and at least the second pulse signal waveforms and the diagnosis information.
 15. The method of claim 14 wherein for each of the number of visits by each of the plurality of subjects, receiving the respective pulse signal information includes receiving the pulse signal information representative of: iii) a third pulse signal waveform captured from the respective subject at a third applied pressure at the first location, the third applied pressured different from the first and the second applied pressures.
 16. The method of claim 15 wherein for a given one of the visits of a given one of the subjects, the received respective pulse signal information further represents a fourth, a fifth and a sixth pulse signal waveform captured from the respective subject at a first, a second and a third applied pressure, respectively, at a second location along a given artery, the second location spaced from the first location.
 17. The method of claim 16 wherein for a given one of the visits of a given one of the subjects, the first, the second and the third pulse signal waveforms are captured temporally proximate to one another.
 18. The method of claim 16 wherein for a given one of the visits of a given one of the subjects, the first, the second, the third, the fourth, the fifth and the sixth pulse signal waveforms are captured temporally proximate to one another.
 19. The method of claim 15 wherein for the given one of the visits of the given one of the subjects, the first, the second and the third pulse signal waveforms represent pulse waveforms captured at a first location along the radial artery proximate a wrist bone on a thumb side of a hand of the subject at the first, the second and the third applied pressures, respectively, and the fourth, the fifth, and the sixth pulse signal waveforms represent pulse waveforms captured at a second location along the radial artery proximate the ulnar, at the first, the second and the third applied pressures, respectively, the second location spaced from the first location.
 20. The method of claim 19 wherein for a given one of the visits of a given one of the subjects, the received respective pulse signal information further represents a seventh, an eight and a ninth pulse signal waveform captured from the respective subject at a first, a second and a third applied pressure, respectively, at a third location along the radial artery, the third location closely spaced from the first and the second locations.
 21. The method of claim 20 wherein for a given one of the visits of a given one of the subjects, the first, the second, the third, the fourth, the fifth, the sixth, the seventh, the eight, and the ninth pulse signal waveforms are captured substantially concurrently with one another.
 22. The method of claim 19 wherein the first, the second and the third pulse signal waveforms each represents respective ones of pulse waveforms captured through a skin of the given subject.
 23. The method of claim 14 wherein the receiving respective pulse signal information includes receiving respective pulse signal information that represents digitized versions of the first and the second pulse signal waveforms.
 24. The method of claim 14, further comprising: digitizing the first and second pulse signal waveforms, by the at least one processor circuit, to generate the respective pulse signal information.
 25. A system to capture diagnostic information, the system comprising: a device, the device comprising: a first pulse waveform transducer response to a pulse to produce a first pulse waveform representation; a second pulse waveform transducer response to a pulse to produce a second pulse waveform representation, the second pulse waveform transducer spaced in use from the first pulse waveform.
 26. The system of claim 25, further comprising: a sleeve or cuff that carries the first and the second pulse waveform transducers, the sleeve or cuff selectively attachable and detachable to a wrist of the subject.
 27. The system of claim 25, further comprising: a third pulse waveform transducer response to a pulse to produce a third pulse waveform representation, the third pulse waveform transducer spaced in use from the first and the second pulse waveform transducer.
 28. The system of claim 25, further comprising: a user input device that in use receives information that specifies at least a primary diagnosis.
 29. The system of claim 25, further comprising: at least one communications port that transmits at least the first and the second pulse waveform representation from the system.
 30. A method of operation in a system to capture diagnostic information, the method comprising: producing a first pulse waveform representation that represents a first pulse waveform detected by a first pulse waveform transducer at a first location along a first artery and a first applied pressure; producing a second pulse waveform representation that represents a second pulse waveform detected by a second pulse waveform transducer at a second location along the first artery and a first applied pressure, the second location spaced from the first location; and transmitting the first pulse waveform representation and the second pulse waveform representation from diagnostic device.
 31. The method of claim 30, the method further comprising: producing a first pulse waveform representation that represents the first pulse waveform detected by a first pulse waveform transducer at the first location along the first artery and a second applied pressure, the second applied pressure different than the first applied pressure; producing a second pulse waveform representation that represents a second pulse waveform detected by a second pulse waveform transducer at the second location along the first artery and a second applied pressure, the second applied pressure different than the first applied pressure.
 32. The method of claim 30, the method further comprising: producing a first pulse waveform representation that represents the first pulse waveform detected by a first pulse waveform transducer at the first location along the first artery and a third applied pressure, the third applied pressure different than the first and the second applied pressure; producing a second pulse waveform representation that represents a second pulse waveform detected by a second pulse waveform transducer at the second location along the first artery and a third applied pressure, the third applied pressure different than the first and the second applied pressure.
 33. The method of claim 32, the method further comprising: producing a third pulse waveform representation that represents a third pulse waveform detected by a third pulse waveform transducer at a third location along a first artery and a first applied pressure, the third location different from the first and the second locations.
 34. The method of claim 33, the method further comprising: producing a third pulse waveform representation that represents a third pulse waveform detected by a third pulse waveform transducer at the third location along the first artery and at a second applied pressure, the second applied pressure different than the first applied pressure.
 35. The method of claim 30, further comprising: receiving information that specifies at least a primary diagnosis via at least one user input device.
 36. The method of claim 35, further comprising: transmitting the received information that specifies at least a primary symptom along with the first pulse waveform representation, the second pulse waveform representation and at least a first applied pressure signal from diagnostic device. 